In a daily life, in a place in which weather phenomena, for example fog, yellow dust, and the like, occur, an outline of an object becomes blurred, and a color of the object is changed. Additionally, an extremely short distance may be recognized, in comparison to a general situation.
In a short viewing distance, traffic inconvenience may occur, and a risk of an accident in all connections, for example vehicles, ships, aircrafts, and the like, may be increased.
In the above situation, when an image is captured, a dynamic range may be reduced, and it is difficult to properly bring a camera into focus, in comparison to looking with human eyes. Accordingly, the viewing distance may be further reduced.
A color of an object in a place in which weather phenomena, for example fog, yellow dust, and the like, occur may be affected by a weather environment, for example fog, yellow dust, and the like, and may be changed in comparison to a general situation. Accordingly, it is difficult to accurately perceive the object.
Because an image obtained by capturing an object in a weather environment, for example fog, yellow dust, and the like, is not determined to depict the object in a lifelike manner. Accordingly, the image may be determined to be damaged, and may be referred to as a damaged image.
FIG. 1 illustrates an example of modeling a process of inputting light to a camera in a foggy situation.
A sensor 101 of the camera may generate an image by a direct transmission, that is, light emitted from a light source 103 and reflected from an object 102.
For example, the image may be damaged by a thick fog 104.
To the sensor 101, a reflect transmission, that is, light emitted from the light source 103 and reflected from the fog 104, as well as the light source 103 may be input. The fog 104 may include fine particles in air.
In other words, the sensor 101 may generate a damaged image by receiving, as inputs, the direct transmission together with the reflect transmission.
An image damaged by a weather environment, for example fog, yellow dust, and the like, may be formed by inputting light reflected by fine particles in air together with light reflected from an object. Accordingly, visibility in the image may be reduced, and colors may be blurred. It may be difficult to recognize and perceive the image.
In a place exposed to a change in a weather environment, for example fog, yellow dust, and the like, an image may not be normally obtained by a surveillance camera, a camera for vehicles, and the like, that are installed outside a building, because the image may be damaged by the weather environment. Accordingly, all functions of the surveillance camera, the camera for vehicles, and the like may be useless.
In other words, due to a damaged image, a camera may not normally operate as a main purpose of installation of the camera, and a large number of functions, for example an image stabilization, a movement detection, prevention of a vehicle collision, road lane recognition, and the like, may not be properly used.
Detection and interpretation of an image damaged by a weather environment, for example fog, yellow dust, and the like, may be omitted, or may not be properly performed. The detection and interpretation may be limited as a technology needing to be used selectively by a user, instead of being automatically used and accordingly, it is impossible to use a camera as a surveillance camera that is not frequently adjusted by a user.
Based on an environment, a situation, and the like in which an image is captured, a performance of a result obtained by recovering the image may be greatly changed. Based on an intensity of a weather environment, for example fog, yellow dust, and the like, an intensity and an arrangement of neighboring light sources, and the like, a performance of a recovery result may be lower than before an application of a technology.
In image processing technologies for recovering a damaged image according to a related art, it is difficult to realize a function, for example surveillance, and the like, in real time.
To recover a damaged image using a technology according to a related art, an iterative and complex algorithm may be applied to a single image, and a relatively long period of time from a few seconds to a few minutes may be required. Accordingly, it is impossible to use the technology according to a related art for real-time visual recording.
Recovering of a damaged image according to a related art may require a considerable amount of hardware for the technical application. A technology requiring a normal image similar to a damaged image, or technologies requiring information other than an input image to recover a single image, for example a technology requiring a plurality of damaged images captured at various angles, a technology requiring an image damaged by various exposures, and the like, may require a considerable amount of time and a considerable amount of hardware.